Data centers refer to facilities used to house computer systems and associated components, such as telecommunications (networking equipment) and storage systems. They generally include redundancy, such as redundant data communications connections and power supplies. These computer systems and associated components generally make up the Internet. A metaphor for the Internet is cloud.
A large number of computers connected through a real-time communication network such as the Internet generally form a cloud. Cloud computing refers to distributed computing over a network, and the ability to run a program or application on many connected computers of one or more clouds at the same time.
The cloud has become one of the, or perhaps even the, most desirable platform for storage and networking. A data center with one or more clouds may have real server hardware, and in fact served up by virtual hardware, simulated by software running on one or more real machines. Such virtual servers do not physically exist and can therefore be moved around and scaled up or down on the fly without affecting the end user, somewhat like a cloud becoming larger or smaller without being a physical object. Cloud bursting refers to a cloud becoming larger or smaller.
The cloud also focuses on maximizing the effectiveness of shared resources, resources referring to machines or hardware such as storage systems and/or networking equipment. Sometimes, these resources are referred to as instances. Cloud resources are usually not only shared by multiple users but are also dynamically reallocated per demand. This can work for allocating resources to users. For example, a cloud computer facility, or a data center, that serves Australian users during Australian business hours with a specific application (e.g., email) may reallocate the same resources to serve North American users during North America's business hours with a different application (e.g., a web server). With cloud computing, multiple users can access a single server to retrieve and update their data without purchasing licenses for different applications.
Cloud computing allows companies to avoid upfront infrastructure costs, and focus on projects that differentiate their businesses instead of infrastructure. It further allows enterprises to get their applications up and running faster, with improved manageability and less maintenance, and enables information technology (IT) to more rapidly adjust resources to meet fluctuating and unpredictable business demands.
Fabric computing or unified computing involves the creation of a computing fabric consisting of interconnected nodes that look like a ‘weave’ or a ‘fabric’ when viewed collectively from a distance. Usually this refers to a consolidated high-performance computing system consisting of loosely coupled storage, networking and parallel processing functions linked by high bandwidth interconnects.
The fundamental components of fabrics are “nodes” (processor(s), memory, and/or peripherals) and “links” (functional connection between nodes). Manufacturers of fabrics include IBM and BROCADE. The latter are examples of fabrics made of hardware. Fabrics are also made of software or a combination of hardware and software.
A traditional data center employed with a cloud may suffer from latency and crashes due to underestimated usage. Furthermore, such a data center may inefficiently use storage and networking systems of the cloud. Perhaps most importantly of all, such a data center may manually deploy applications. Application deployment services may be performed, in large part, manually with elaborate infrastructure and/or numerous teams of professionals, and potential failures due to unexpected bottlenecks. Some of the foregoing translate to high costs. Lack of automation results in delays in launching business applications. It is estimated that application delivery services currently consume approximately thirty percent of the time required for deployment operations. Additionally, scalability of applications across multiple clouds is nearly nonexistent.
There is therefore a need for a method and apparatus to decrease bottleneck, latency, infrastructure, and costs while increasing efficiency and scalability of a data center.